Application of ARIMA product seasonal model in predicting incidence of hand foot and mouth disease in Yancheng

Objective To explore the feasibility of multiple seasonal autoregressive integrated moving average (ARIMA) product seasonal model in predicting the incidence of hand, foot and mouth disease (HFMD) in Yancheng. Methods The ARIMA product seasonal model was established based on monthly incidence rates of HFMD in Yancheng from January 2009 to December 2015. Results Through the tests of parameters and goodness of fit as well as white-noise residuals, we finalized the model ARIMA(1, 0, 1)(1, 1, 0)12, of which the normalized BIC was 2.997, Ljung-Box was 20.692(P0.05), the model could fit the incidence trend over the period, the values were in 95% confidence interval and the mean error rate was 41.296%. The mean error rate of another checking model was 23.998%. The prediction accuracy was better than fitting accuracy. Conclusion The model can be used to predict the incidence trend of HFMD in Yancheng, which might play a positive role in the prevention and control of HFMD.